TDOT RDS Data Quality Assurance and High-Resolution Content Enhancement
The project focuses on addressing data quality and integrity challenges in the use of roadside radar detector data, the primary source of fixed sensor traffic data in Tennessee. The project aims to standardize sensor configurations, audit data quality, and establish a robust framework for roadside radar data utilization.
Roadside radar traffic sensors can be high-quality data sources that provide traffic volume and speed in near-real time. However, the large network of over 600 sensors across Tennessee imposes difficulties in data consistency and quality, which make corridor-level traffic data analysis challenging.
Detector standardization is a mostly manual process that is aided by spatiotemporal outlier detection and geospatial metadata for sensor locations. Intrinsic sensor configuration and extrinsic data organization must both be addressed to ensure each sensor is reporting accruately based on its installation. After this level of consistency is acheived, traffic detection and quantification on major Tennessee highway corridors can be performed with confidence.
Physical traffic sensors still have a place in today's traffic sensing landscape due to their ability to observe nearly all vehicles on the roadway instead of relying on a sparse sample. If sensor data quality can be standardized and improved, they can serve as a much more reliable data source than cloud-based traffic sensing and provide insight into incident management, long-range transportation planning, and corridor management.
The project has, thus far, made large strides in addressing data shortcomings across the state. Prototype data visualizations are being made available to traffic management center (TMC) operators, who coordinate incident response and management activities. Further imporvements are under way that will unlock freight analysis on Tennessee highways.
